Prepare Exam With Latest Snowflake DEA-C01 Exam Questions

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Snowflake SnowPro Advanced: Data Engineer Certification Exam Sample Questions (Q157-Q162):

NEW QUESTION # 157
A finance company receives data from third-party data providers and stores the data as objects in an Amazon S3 bucket.
The company ran an AWS Glue crawler on the objects to create a data catalog. The AWS Glue crawler created multiple tables. However, the company expected that the crawler would create only one table.
The company needs a solution that will ensure the AVS Glue crawler creates only one table.
Which combination of solutions will meet this requirement? (Choose two.)

Answer: B,E


NEW QUESTION # 158
As part of Table Designing, Data Engineer added a timestamp column that inserts the current timestamp as the default value as records are loaded into a table. The intent is to capture the time when eachrecord was loaded into the table; however, the timestamps are earlier than the LOAD_TIME column values returned by COPY_HISTORY view (Account Usage). What could be reason of this issue?

Answer: A

Explanation:
Explanation
The reason timestamps are earlier than the LOAD_TIME column values which is returned by COPY_HISTORY view (Account Usage) is that CURRENT_TIMESTAMP is evaluated when the load operation is compiled in cloud services rather than when the record is inserted into the table (i.e. when the transaction for the load operation is committed).


NEW QUESTION # 159
A data engineer creates an AWS Glue Data Catalog table by using an AWS Glue crawler that is named Orders. The data engineer wants to add the following new partitions:
s3://transactions/orders/order_date=2023-01-01
s3://transactions/orders/order_date=2023-01-02
The data engineer must edit the metadata to include the new partitions in the table without scanning all the folders and files in the location of the table.
Which data definition language (DDL) statement should the data engineer use in Amazon Athena?

Answer: D

Explanation:
https://docs.aws.amazon.com/athena/latest/ug/alter-table-add-partition.html


NEW QUESTION # 160
Stuart, a Lead Data Engineer in MACRO Data Company created streams on set of External tables. He has been asked to extend the data retention period of the stream for 90 days, which parameter he can utilize to enable this extension?

Answer: B

Explanation:
Explanation
External tables do not have data retention period applicable.
Good to Understand other Options available.
DATA_RETENTION_TIME_IN_DAYS
Type: Object (for databases, schemas, and tables) - Can be set for Account - Database - Schema - Table Description: Number of days for which Snowflake retains historical data for performing Time Trav-el actions (SELECT, CLONE, UNDROP) on the object. A value of 0 effectively disables Time Travel for the specified database, schema, or table.
Values:
0 or 1 (for Standard Edition)
0 to 90 (for Enterprise Edition or higher)
Default:
1
MAX_DATA_EXTENSION_TIME_IN_DAYS
Type: Object (for databases, schemas, and tables) - Can be set for Account - Database - Schema - Table Description: Maximum number of days for which Snowflake can extend the data retention period for tables to prevent streams on the tables from becoming stale. By default, if the DA-TA_RETENTION_TIME_IN_DAYS setting for a source table is less than 14 days, and a stream has not been consumed, Snowflake temporarily extends this period to the stream's offset, up to a maximum of 14 days, regardless of the Snowflake Edition for your account. The MAX_DATA_EXTENSION_TIME_IN_DAYS parameter enables you to limit this automatic ex-tension period to control storage costs for data retention or for compliance reasons.
This parameter can be set at the account, database, schema, and table levels. Note that setting the parameter at the account or schema level only affects tables for which the parameter has not already been explicitly set at a lower level (e.g. at the table level by the table owner). A value of 0 effective-ly disables the automatic extension for the specified database, schema, or table.
Values:
0 to 90 (i.e. 90 days) - a value of 0 disables the automatic extension of the data retention period. To increase the maximum value for tables in your account, Client needs to contact Snowflake Sup-port.
Default:14


NEW QUESTION # 161
A company uses Amazon Redshift as its data warehouse. Data encoding is applied to the existing tables of the data warehouse. A data engineer discovers that the compression encoding applied to some of the tables is not the best fit for the data.
The data engineer needs to improve the data encoding for the tables that have sub-optimal encoding.
Which solution will meet this requirement?

Answer: D

Explanation:
The ANALYZE COMPRESSION command in Amazon Redshift evaluates the existing data in a table and suggests the most optimal compression encoding for each column. After running this command, the data engineer can manually update the table to apply the recommended compression encodings. This approach ensures the best fit for data compression, improving storage efficiency and query performance.
The ANALYZE command collects statistics for query optimization, but it does not provide compression encoding recommendations. It is focused on query performance, not data compression.
The VACUUM REINDEX command does not exist in Amazon Redshift. VACUUM commands are generally used for reclaiming disk space and sorting tables, not for compression optimization.
VACUUM RECLUSTER does not exist in Amazon Redshift. VACUUM operations focus on reorganizing and sorting data but do not address compression encoding.


NEW QUESTION # 162
......

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